Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Lime Scribe stands out as an ambient AI scribe specifically tailored for home health and hospice organizations, offering a distinct advantage over traditional physician-office scribes like Suki, Nuance DAX, and DeepScribe by focusing on the unique requirements of OASIS-E2, HOPE, PDGM, and the specific workflows utilized by post-acute care clinicians. The key feature of Lime Scribe is that every chart undergoes verification by a certified home health coder prior to being uploaded to your electronic health record (EHR), ensuring that while AI effectively captures the visit details, a qualified professional carefully checks OASIS items, ICD-10 codes, and all pertinent visit information, with this quality assurance included as standard rather than an additional cost.
Key functionalities include:
- Ambient AI that seamlessly captures OASIS-E2, HOPE, and visit notes during natural encounters
- Verification of ICD-10 coding by skilled coders, ensuring compliance with PDGM and readiness for audits
- Real-time quality assurance for OASIS that identifies errors in Section GG and gaps in social determinants of health (SDOH)
- Automation of admissions intake, which effectively parses referrals and confirms eligibility
- Seamless integration with major EMR systems such as HCHB, WellSky, MatrixCare, Axxess, DSL, Netsmart, and KanTime.
Compliant with HIPAA regulations and supported by signed Business Associate Agreements (BAAs), Lime Scribe has successfully processed over 30,000 charts annually and boasts an impressive clinician rating of 4.9 stars. This makes it a reliable choice for agencies looking to enhance their documentation processes while maintaining high standards of accuracy and compliance.
Description
The Oasis Loss Modelling Framework (Oasis LMF) serves as an open-source platform for catastrophe modeling that aims to improve risk assessment through its commitment to transparency, performance, and innovation. Founded as a not-for-profit entity, Oasis LMF provides a wide array of tools for the creation, deployment, and operation of catastrophe models, allowing for flexibility in modeling methods. The platform features a user-friendly web interface and an API that ensures easy integration with various systems, enhancing interoperability and user experience. Key components like Oasis ktools facilitate the large-scale execution of catastrophe models, while the Oasis Model Development Toolkit aids in the creation and testing of new models. With a strong focus on collaboration within the community, Oasis LMF boasts an ecosystem that includes over 18 suppliers and more than 90 different models, promoting a rich and varied modeling landscape. This diverse array of resources underscores the platform's mission to support users in navigating the complexities of risk assessment in an ever-evolving environment.
API Access
Has API
API Access
Has API
Integrations
HurLoss
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Lime Health
Founded
2025
Country
United States
Website
getlimeai.com
Vendor Details
Company Name
Oasis Loss Modelling Framework
Founded
2012
Country
United Kingdom
Website
oasislmf.org
Product Features
Home Health Care
Billing & Invoicing
Charting
Electronic Signature
Employee Tracking
Medication Database
Patient Intake
Scheduling
Time / Task Reporting
Medical Transcription
Abbreviation Expansion
Archiving & Retention
Audio File Management
Audio Transmission
Customizable Macros
Transcription Reporting
Voice Capture
Voice Recognition